• DocumentCode
    1141108
  • Title

    On the VLSI implementation of real-time order statistic filters

  • Author

    Murthy, N. Rama ; Swamy, M.N.S.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada
  • Volume
    40
  • Issue
    5
  • fYear
    1992
  • fDate
    5/1/1992 12:00:00 AM
  • Firstpage
    1241
  • Lastpage
    1252
  • Abstract
    Real-time implementation of an order-statistic filter (OSF) or ranked order filter requires the computation of the order statistic (ranked order) of the samples in a window which gets periodically updated with the arrival of a new sample(s). The authors give an algorithm for the computation of the running order statistic. A highly parallel architecture suitable for VLSI implementation is presented. The architecture is very versatile, with programmable window size and rank order. An expansion algorithm and its VLSI architecture, which permit the usage of two r-bit OSFs to implement an (r+1)-bit OSF, where r is the resolution of the input signal samples, are given. In a special case where one is satisfied with at most one LSB error, the hardware complexity of the proposed architecture can be reduced by almost one half. It is further shown how a VLSI chip incorporating the proposed architecture can be used as the basic building block in the real-time implementation of other forms of nonlinear filters
  • Keywords
    VLSI; digital filters; parallel algorithms; parallel architectures; real-time systems; VLSI; digital filters; expansion algorithm; input signal samples; nonlinear filters; parallel architecture; programmable window size; ranked order filter; real-time order statistic filters; resolution; running order statistic; Adaptive filters; Computer architecture; Digital filters; Filtering; Image processing; Parallel architectures; Signal processing; Signal resolution; Statistics; Very large scale integration;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.134486
  • Filename
    134486